class ov::Node¶
Overview¶
Nodes are the backbone of the graph of Value dataflow. Every node has zero or more nodes as arguments and one value, which is either a tensor or a (possibly empty) tuple of values. More…
#include <node.hpp>
class Node: public std::enable_shared_from_this< Node >
{
public:
// typedefs
typedef DiscreteTypeInfo type_info_t;
typedef std::map<std::string, Any> RTMap;
// methods
virtual void validate_and_infer_types();
void constructor_validate_and_infer_types();
virtual bool visit_attributes(AttributeVisitor&);
virtual const ov::op::AutoBroadcastSpec& get_autob() const;
virtual bool has_evaluate() const;
virtual bool evaluate(
const ov::HostTensorVector& output_values,
const ov::HostTensorVector& input_values
) const;
virtual bool evaluate(
const ov::HostTensorVector& output_values,
const ov::HostTensorVector& input_values,
const EvaluationContext& evaluationContext
) const;
virtual bool evaluate_lower(const ov::HostTensorVector& output_values) const;
virtual bool evaluate_upper(const ov::HostTensorVector& output_values) const;
virtual bool evaluate(
ov::TensorVector& output_values,
const ov::TensorVector& input_values
) const;
virtual bool evaluate(
ov::TensorVector& output_values,
const ov::TensorVector& input_values,
const ov::EvaluationContext& evaluationContext
) const;
virtual bool evaluate_lower(ov::TensorVector& output_values) const;
virtual bool evaluate_upper(ov::TensorVector& output_values) const;
virtual bool evaluate_label(TensorLabelVector& output_labels) const;
virtual bool constant_fold(
OutputVector& output_values,
const OutputVector& inputs_values
);
virtual OutputVector decompose_op() const;
virtual const type_info_t& get_type_info() const = 0;
const char \* get_type_name() const;
void set_arguments(const NodeVector& arguments);
void set_arguments(const OutputVector& arguments);
void set_argument(size_t position, const Output<Node>& argument);
void set_output_type(
size_t i,
const element::Type& element_type,
const PartialShape& pshape
);
void set_output_size(size_t output_size);
void invalidate_values();
virtual void revalidate_and_infer_types();
virtual std::string description() const;
const std::string& get_name() const;
void set_friendly_name(const std::string& name);
const std::string& get_friendly_name() const;
virtual bool is_dynamic() const;
size_t get_instance_id() const;
virtual std::ostream& write_description(std::ostream& os, uint32_t depth = 0) const;
const std::vector<std::shared_ptr<Node>>& get_control_dependencies() const;
const std::vector<Node \*>& get_control_dependents() const;
void add_control_dependency(std::shared_ptr<Node> node);
void remove_control_dependency(std::shared_ptr<Node> node);
void clear_control_dependencies();
void clear_control_dependents();
void add_node_control_dependencies(std::shared_ptr<Node> source_node);
void add_node_control_dependents(std::shared_ptr<Node> source_node);
void transfer_control_dependents(std::shared_ptr<Node> replacement);
size_t get_output_size() const;
const element::Type& get_output_element_type(size_t i) const;
const element::Type& get_element_type() const;
const Shape& get_output_shape(size_t i) const;
const PartialShape& get_output_partial_shape(size_t i) const;
Output<const Node> get_default_output() const;
Output<Node> get_default_output();
virtual size_t get_default_output_index() const;
size_t no_default_index() const;
const Shape& get_shape() const;
descriptor::Tensor& get_output_tensor(size_t i) const;
descriptor::Tensor& get_input_tensor(size_t i) const;
const std::string& get_output_tensor_name(size_t i) const;
std::set<Input<Node>> get_output_target_inputs(size_t i) const;
size_t get_input_size() const;
const element::Type& get_input_element_type(size_t i) const;
const Shape& get_input_shape(size_t i) const;
const PartialShape& get_input_partial_shape(size_t i) const;
const std::string& get_input_tensor_name(size_t i) const;
Node \* get_input_node_ptr(size_t index) const;
std::shared_ptr<Node> get_input_node_shared_ptr(size_t index) const;
Output<Node> get_input_source_output(size_t i) const;
virtual std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& inputs) const = 0;
std::shared_ptr<Node> copy_with_new_inputs(const OutputVector& new_args) const;
std::shared_ptr<Node> copy_with_new_inputs(
const OutputVector& inputs,
const std::vector<std::shared_ptr<Node>>& control_dependencies
) const;
bool has_same_type(std::shared_ptr<const Node> node) const;
RTMap& get_rt_info();
const RTMap& get_rt_info() const;
NodeVector get_users(bool check_is_used = false) const;
virtual size_t get_version() const;
virtual std::shared_ptr<Node> get_default_value() const;
bool operator < (const Node& other) const;
std::vector<Input<Node>> inputs();
std::vector<Input<const Node>> inputs() const;
std::vector<Output<Node>> input_values() const;
std::vector<Output<Node>> outputs();
std::vector<Output<const Node>> outputs() const;
Input<Node> input(size_t input_index);
Input<const Node> input(size_t input_index) const;
Output<Node> input_value(size_t input_index) const;
Output<Node> output(size_t output_index);
Output<const Node> output(size_t output_index) const;
OPENVINO_SUPPRESS_DEPRECATED_START void set_op_annotations(std::shared_ptr<ngraph::op::util::OpAnnotations> op_annotations);
std::shared_ptr<ngraph::op::util::OpAnnotations> get_op_annotations() const;
virtual OPENVINO_SUPPRESS_DEPRECATED_END bool match_value(
ov::pass::pattern::Matcher \* matcher,
const Output<Node>& pattern_value,
const Output<Node>& graph_value
);
virtual bool match_node(
ov::pass::pattern::Matcher \* matcher,
const Output<Node>& graph_value
);
};
// direct descendants
class ExecutionNode;
class Op;
class Pattern;
Detailed Documentation¶
Nodes are the backbone of the graph of Value dataflow. Every node has zero or more nodes as arguments and one value, which is either a tensor or a (possibly empty) tuple of values.
Methods¶
virtual void validate_and_infer_types()
Verifies that attributes and inputs are consistent and computes output shapes and element types. Must be implemented by concrete child classes so that it can be run any number of times.
Throws if the node is invalid.
virtual const ov::op::AutoBroadcastSpec& get_autob() const
Returns:
the autobroadcasr spec
virtual bool has_evaluate() const
Allows to get information about availability of evaluate method for the current operation.
virtual bool evaluate(
const ov::HostTensorVector& output_values,
const ov::HostTensorVector& input_values
) const
Evaluates the op on input_values putting results in output_values.
Deprecated Use evaluate with ov::Tensor instead
Parameters:
output_values |
Tensors for the outputs to compute. One for each result |
input_values |
Tensors for the inputs. One for each inputs. |
Returns:
true if successful
virtual bool evaluate(
const ov::HostTensorVector& output_values,
const ov::HostTensorVector& input_values,
const EvaluationContext& evaluationContext
) const
Evaluates the op on input_values putting results in output_values.
Deprecated Use evaluate with ov::Tensor instead
Parameters:
output_values |
Tensors for the outputs to compute. One for each result |
input_values |
Tensors for the inputs. One for each inputs. |
evaluation_context |
Storage of additional settings and attributes that can be used when evaluating the op. |
Returns:
true if successful
virtual bool evaluate(
ov::TensorVector& output_values,
const ov::TensorVector& input_values
) const
Evaluates the op on input_values putting results in output_values.
Parameters:
output_values |
Tensors for the outputs to compute. One for each result |
input_values |
Tensors for the inputs. One for each inputs. |
Returns:
true if successful
virtual bool evaluate(
ov::TensorVector& output_values,
const ov::TensorVector& input_values,
const ov::EvaluationContext& evaluationContext
) const
Evaluates the op on input_values putting results in output_values.
Parameters:
output_values |
Tensors for the outputs to compute. One for each result |
input_values |
Tensors for the inputs. One for each inputs. |
evaluation_context |
Storage of additional settings and attributes that can be used when evaluating the op. |
Returns:
true if successful
virtual OutputVector decompose_op() const
Decomposes the FusedOp into a sub-graph consisting of core openvino ops.
Returns:
A vector of nodes comprising the sub-graph. The order of output tensors must match the match output tensors of the FusedOp
virtual const type_info_t& get_type_info() const = 0
Returns the NodeTypeInfo for the node’s class. During transition to type_info, returns a dummy type_info for Node if the class has not been updated yet.
void set_arguments(const NodeVector& arguments)
Sets/replaces the arguments with new arguments.
void set_arguments(const OutputVector& arguments)
Sets/replaces the arguments with new arguments.
void set_argument(size_t position, const Output<Node>& argument)
Sets/replaces the arguments with new arguments.
void set_output_size(size_t output_size)
Sets the number of outputs.
virtual std::string description() const
Get the string name for the type of the node, such as Add
or Multiply
. The class name, must not contain spaces as it is used for codegen.
Returns:
A const reference to the node’s type name
const std::string& get_name() const
Get the unique name of the node.
Returns:
A const reference to the node’s unique name.
void set_friendly_name(const std::string& name)
Sets a friendly name for a node. This does not overwrite the unique name of the node and is retrieved via get_friendly_name(). Used mainly for debugging. The friendly name may be set exactly once.
Parameters:
name |
is the friendly name to set |
const std::string& get_friendly_name() const
Gets the friendly name for a node. If no friendly name has been set via set_friendly_name then the node’s unique name is returned.
Returns:
A const reference to the node’s friendly name.
virtual std::ostream& write_description(std::ostream& os, uint32_t depth = 0) const
Writes a description of a node to a stream.
Parameters:
os |
The stream; should be returned |
depth |
How many levels of inputs to describe |
Returns:
The stream os
const std::vector<std::shared_ptr<Node>>& get_control_dependencies() const
Get control dependencies registered on the node.
const std::vector<Node \*>& get_control_dependents() const
Get nodes dependent on this node.
void add_control_dependency(std::shared_ptr<Node> node)
This node cannot execute until node executes.
void remove_control_dependency(std::shared_ptr<Node> node)
Remove the dependency of this node on node.
void clear_control_dependencies()
Remove all dependencies from this node.
void clear_control_dependents()
Remove this node as a dependency from all dependent nodes.
void add_node_control_dependencies(std::shared_ptr<Node> source_node)
This node absorbs the control dependencies of source_node.
void add_node_control_dependents(std::shared_ptr<Node> source_node)
This node becomes a dependent of every node dependent on source_node.
void transfer_control_dependents(std::shared_ptr<Node> replacement)
This node’s control dependencies are replaced by replacement.
size_t get_output_size() const
Returns the number of outputs from the node.
const element::Type& get_output_element_type(size_t i) const
Returns the element type for output i.
const element::Type& get_element_type() const
Checks that there is exactly one output and returns its element type.
const Shape& get_output_shape(size_t i) const
Returns the shape for output i.
const PartialShape& get_output_partial_shape(size_t i) const
Returns the partial shape for output i.
Output<const Node> get_default_output() const
Return the output to use when converting to an Output<Node> with no index specified. Throws when not supported.
virtual size_t get_default_output_index() const
Returns the output of the default output, or throws if there is none.
size_t no_default_index() const
Throws no default.
const Shape& get_shape() const
Checks that there is exactly one output and returns its shape.
descriptor::Tensor& get_output_tensor(size_t i) const
Returns the tensor for output or input i.
const std::string& get_output_tensor_name(size_t i) const
Returns the tensor name for output i.
size_t get_input_size() const
Returns the number of inputs for the op.
const element::Type& get_input_element_type(size_t i) const
Returns the element type of input i.
const Shape& get_input_shape(size_t i) const
Returns the shape of input i.
const PartialShape& get_input_partial_shape(size_t i) const
Returns the partial shape of input i.
const std::string& get_input_tensor_name(size_t i) const
Returns the tensor name for input i.
bool has_same_type(std::shared_ptr<const Node> node) const
True if this and node have one output with same element type and shape.
NodeVector get_users(bool check_is_used = false) const
Get all the nodes that uses the current node.
virtual size_t get_version() const
Returns:
Version of this node
bool operator < (const Node& other) const
Use instance ids for comparison instead of memory addresses to improve determinism.
std::vector<Input<Node>> inputs()
Returns:
A vector containing a handle for each of this node’s inputs, in order.
std::vector<Input<const Node>> inputs() const
Returns:
A vector containing a handle for each of this node’s inputs, in order.
std::vector<Output<Node>> input_values() const
Returns:
A vector containing the values for each input
std::vector<Output<Node>> outputs()
Returns:
A vector containing a handle for each of this node’s outputs, in order.
std::vector<Output<const Node>> outputs() const
Returns:
A vector containing a handle for each of this node’s outputs, in order.
Input<Node> input(size_t input_index)
Parameters:
std::out_of_range |
if the node does not have at least |
Returns:
A handle to the input_index
th input of this node.
Input<const Node> input(size_t input_index) const
Parameters:
std::out_of_range |
if the node does not have at least |
Returns:
A handle to the input_index
th input of this node.
Output<Node> output(size_t output_index)
Parameters:
std::out_of_range |
if the node does not have at least |
Returns:
A handle to the output_index
th output of this node.
Output<const Node> output(size_t output_index) const
Parameters:
std::out_of_range |
if the node does not have at least |
Returns:
A handle to the output_index
th output of this node.